Underwater target detection and tracking based on array element domain data from multi-arrays

An algorithm of underwater target detection and tracking based on array element domain data from multiarrays is presented in order to improve the target detection and tracking ability in the complex marine environment.Sequential Markov chain Monte Carlo method is used to sample and update the target parameters.By decomposing the posterior probability and sampling function in the received likelihood ratio,and calculating the joint likelihood function of the sampled particles according to the multi-array element domain data,a joint estimate of the target number and states is achieved during the iterative process.The research results show that the average positioning error of the single target can be stabilized within 50 m at a high SNR,the new and vanishing targets can be effectively detected under the situation of multiple targets going in and out randomly,and both the weak targets and crosses targets can achieve effective detection and tracking.The simulation and Sea trial results show that the algorithm is able to detect and track the targets functionally.